Ventricular tachycardia (VT) is a potentially lethal arrhythmia which most often occurs in the setting of chronic coronary artery disease. This arrhythmia is virtually always associated with hemodynamic compormise and not infrequently precipitates sudden cardiac death. Empiric therapy has failed to prevent recurrences of VT and sudden death. A greater understanding of the mechanism of this arrhythmia and the electrophysiologic substrates required for its presence would allow for the development of a more rational approach to its therapy. The goals of this proposal are to evaluate the electrophysiologic substrates of VT by activation mapping of the ventricles during sinus rhythm and ventricular pacing, and correlate the activation time, numberof fractionated electrograms, duration of electrograms, and dispersion of refractory periods with: a) the ability to initiate, b) the mode of initiation, and c) the site of origin ov VT. We hope to demonstrate that patients with inducible sustained VT will have more marked specific abnormalities of ventricular activation (i.e., number oand duration of fractionated electrograms) and refractoriness than patients without VT. In addition, we hope to show that the greater the abnormaliites during sinus rhythm, the easier VT can be initiated. The presence of such findings may localize the origin of VT and obviate the need for inducing and mapping all tachycardia morphologies prior to or during surgery. Furthermore, we hope to demonstrate that it is these specific abnormalities which are detected by signal averaging of the surface ECG. Validation of the ability of signal averaging to detect electrograms specifically related to areas responsible for VT would support the use of this non invasive technique to predict patients at risk for this arrhythmia and assess pharmacologic interventions without the need to repeatedly induce the tachycardia by programmed stimulation. The results of this proposal might provide the ability to localize tachycardia origin without induction and mapping as well as to predict patients at risk for tachycardia, both of which would be major advances in our understanding and prevention of sudden cardiac death.